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https://issues.apache.org/jira/browse/IMPALA-11504?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17608227#comment-17608227
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yx91490 edited comment on IMPALA-11504 at 9/25/22 7:14 AM:
-----------------------------------------------------------
I make a test to test performance improvement:
dataset:
{code:java}
CREATE TABLE t (
d1 DECIMAL(19, 3),
d2 DECIMAL(19, 3)
) STORED AS PARQUET;
-- generate random data
INSERT OVERWRITE t
SELECT
cast(rand() * 1000 as DECIMAL(19, 3)) AS d1,
-- prevent divide 0
cast((rand(unix_timestamp()) +1) * 1000000 as DECIMAL(19, 3)) AS d2
FROM tpcds.customer t1,
tpcds.customer t2 LIMIT 50000000;{code}
test SQL:
{code:java}
SELECT count(d1/d2) FROM t; {code}
result:
||version||cost time||
|original edition|16s|
|optimized edition|7s|
was (Author: yx91490):
I make a test to test performance improvement:
dataset:
{code:java}
CREATE TABLE t (
d1 DECIMAL(19, 3),
d2 DECIMAL(19, 3)
) STORED AS PARQUET;
-- generate random data
INSERT OVERWRITE t
SELECT
cast(rand() * 1000 as DECIMAL(19, 3)) AS d1,
-- prevent divide 0
cast((rand(unix_timestamp()) +1) * 1000000 as DECIMAL(19, 3)) AS d2
FROM tpcds.customer t1,
tpcds.customer t2 LIMIT 50000000;{code}
test SQL:
{code:java}
SELECT count(d1/d2) FROM t; {code}
result:
||version||cost time||
|origin edition|16s|
|optimized edition|7s|
> Speed up Decimal16Value division by specializing
> DecimalUtil::GetScaleMultiplier<int256_t>()
> --------------------------------------------------------------------------------------------
>
> Key: IMPALA-11504
> URL: https://issues.apache.org/jira/browse/IMPALA-11504
> Project: IMPALA
> Issue Type: Improvement
> Reporter: yx91490
> Assignee: yx91490
> Priority: Major
>
> There exists a call chain:
> {code:java}
> DecimalValue<int128_t>::Divide() ->
> DecimalUtil::MultiplyByScale<int256_t>() ->
> DecimalUtil::GetScaleMultiplier(){code}
> but decimal-util.h didn't specialize
> DecimalUtil::GetScaleMultiplier<int256_t>(), causing more performance loss.
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